Discovery of SARS-CoV-2 M <sup>pro</sup> Peptide Inhibitors from Modelling Substrate and Ligand Binding

H. T. Henry Chan(Mansfield University), Marc A. Moesser(University of Oxford), Rebecca K. Walters(University of Bristol), Tika R. Malla(Mansfield University), Rebecca M. Twidale(University of Bristol), Tobias John(Mansfield University), Helen M. Deeks(University of Bristol), Tristan Johnston-Wood(Mansfield University), Victor A. Mikhailov(Mansfield University), Richard B. Sessions(University of Bristol), William Harbutt Dawson(RIKEN Center for Computational Science), E. Salah(Mansfield University), Petra Lukacik(Diamond Light Source), Claire Strain‐Damerell(Diamond Light Source), David Owen(Diamond Light Source), Takahito Nakajima(RIKEN Center for Computational Science), Katarzyna Świderek(Universitat Jaume I), Alessio Lodola(University of Parma), Vicent Moliner(Universitat Jaume I), David R. Glowacki(University of Bristol), Martin Walsh(Diamond Light Source), Christopher J. Schofield(Mansfield University), Luigi Genovese(Commissariat à l'Énergie Atomique et aux Énergies Alternatives), Deborah K. Shoemark(University of Bristol), Adrian J. Mulholland(University of Bristol), Fernanda Duarte(Mansfield University), Garrett M. Morris(University of Oxford)
bioRxiv (Cold Spring Harbor Laboratory)
June 19, 2021
Cited by 5Open Access
Full Text

Abstract

The main protease (M pro ) of SARS-CoV-2 is central to its viral lifecycle and is a promising drug target, but little is known concerning structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of classical molecular mechanics and quantum mechanical techniques, including automated docking, molecular dynamics (MD) simulations, linear-scaling DFT, QM/MM, and interactive MD in virtual reality, to investigate the molecular features underlying recognition of the natural M pro substrates. Analyses of the subsite interactions of modelled 11-residue cleavage site peptides, ligands from high-throughput crystallography, and designed covalently binding inhibitors were performed. Modelling studies reveal remarkable conservation of hydrogen bonding patterns of the natural M pro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular at the P2/S2 sites. The binding modes of the natural substrates, together with extensive interaction analyses of inhibitor and fragment binding to M pro , reveal new opportunities for inhibition. Building on our initial M pro -substrate models, computational mutagenesis scanning was employed to design peptides with improved affinity and which inhibit M pro competitively. The combined results provide new insight useful for the development of M pro inhibitors.


Related Papers

No related papers found

Powered by citation graph analysis